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This book constitutes the refereed proceedings of the 10th International Conference on Simulation of Adaptive Behavior, SAB 2008, held in Osaka, Japan in July 2008. The 30 revised full papers and 21 revised poster papers presented were carefully reviewed and selected from 110 submissions. The papers are organized in topical sections on the animat approach to adaptive behaviour, evolution, navigation and internal world models, perception and control, learning and adaptation, cognition, emotion and behaviour, collective and social behaviours, adaptive behaviour in language and communication, and applied adaptive behaviour.
The Animals to Animats Conference brings together researchers fromethology, psychology, ecology, artificial intelligence, artificiallife, robotics, engineering, and related fields to furtherunderstanding of the behaviors and underlying mechanisms that allownatural and synthetic agents (animats) to adapt and survive inuncertain environments The Animals to Animats Conference brings together researchers from ethology, psychology, ecology, artificial intelligence, artificial life, robotics, engineering, and related fields to further understanding of the behaviors and underlying mechanisms that allow natural and synthetic agents (animats) to adapt and survive in uncertain environments. The work presented focuses on well-defined models--robotic, computer-simulation, and mathematical--that help to characterize and compare various organizational principles or architectures underlying adaptive behavior in both natural animals and animats.
From Animals to Animats 4 brings together the latest research at the frontier of an exciting new approach to understanding intelligence.
August 8-12, 1994, Brighton, England From Animals to Animats 3 brings together research intended to advance the fron tier of an exciting new approach to understanding intelligence. The contributors represent a broad range of interests from artificial intelligence and robotics to ethology and the neurosciences. Unifying these approaches is the notion of "animat" -- an artificial animal, either simulated by a computer or embodied in a robot, which must survive and adapt in progressively more challenging environments. The 58 contributions focus particularly on well-defined models, computer simulations, and built robots in order to help characterize and compare various principles and architectures capable of inducing adaptive behavior in real or artificial animals. Topics include: - Individual and collective behavior. - Neural correlates of behavior. - Perception and motor control. - Motivation and emotion. - Action selection and behavioral sequences. - Ontogeny, learning, and evolution. - Internal world models and cognitive processes. - Applied adaptive behavior. - Autonomous robots. - Heirarchical and parallel organizations. - Emergent structures and behaviors. - Problem solving and planning. - Goal-directed behavior. - Neural networks and evolutionary computation. - Characterization of environments. A Bradford Book
Robotics is an exciting field in engineering and natural sciences. Robotics has already made a significant contribution to many industries with the widespread use of industrial robots for tasks such as assembly, welding, painting, and handling materials. In parallel, we have witnessed the emergence of special robots which can undertake assistive jobs, such as search and rescue, de-mining, surveillance, exploration, and security functions. Indeed, the interest in mobile machines, such as climbing and walking robots, has broadened the scope of investigation in robotics. This volume covers broad topics related to mobile machines in general, and climbing and walking robots in particular. Papers from the following keynote speakers are included: Heinz Worn (University of Karlsruhe, Germany), Atsuo Takanishi (University of Waseda, Japan), John Billingsley (University of Southern Queensland, Australia), Bryan Bridge (London South Bank University, UK) and Neville Hogan (Massachusetts Institute of Technology, USA).
New research on the adaptive behavior of natural and synthetic agents.
Studies on robotics applications have grown substantially in recent years, with swarm robotics being a relatively new area of research. Inspired by studies in swarm intelligence and robotics, swarm robotics facilitates interactions between robots as well as their interactions with the environment. The Handbook of Research on Design, Control, and Modeling of Swarm Robotics is a collection of the most important research achievements in swarm robotics thus far, covering the growing areas of design, control, and modeling of swarm robotics. This handbook serves as an essential resource for researchers, engineers, graduates, and senior undergraduates with interests in swarm robotics and its applications.
Reaching for objects in our surroundings is an everyday activity that most humans perform seamlessly a hundred times a day. It is nonetheless a complex behavior that requires the perception of objects’ features, action selection, movement planning, multi-joint coordination, force regulation, and the integration of all of these properties during the actions themselves to meet the successful demands of extremely varied task goals. Even though reach-to-grasp behavior has been studied for decades, it has, in recent years, become a particularly growing area of multidisciplinary research because of its crucial role in activities of daily living and broad range of applications to other fields, including physical rehabilitation, prosthetics, and robotics. This volume brings together novel and exciting research that sheds light into the complex sensory-motor processes involved in the selection and production of reach-to-grasp behaviors. It also offers a unique life-span and multidisciplinary perspective on the development and multiple processes involved in the formation of reach-to-grasp. It covers recent and exciting discoveries from the fields of developmental psychology and learning sciences, neurophysiology and brain sciences, movement sciences, and the dynamic field of developmental robotics, which has become a very active applied field relying on biologically inspired models. This volume is a rich and valuable resource for students and professionals in all of these research fields, as well as cognitive sciences, rehabilitation, and other applied sciences.
The burgeoning field of social neuroscience has begun to illuminate the complex biological bases of human social cognitive abilities. However, in spite of being based on the premise of investigating the neural bases of interacting minds, the majority of studies have focused on studying brains in isolation using paradigms that investigate offline social cognition, i.e. social cognition from a detached observer's point of view, asking study participants to read out the mental states of others without being engaged in interaction with them. Consequently, the neural correlates of real-time social interaction have remained elusive and may —paradoxically— represent the 'dark matter' of social neuroscience. More recently, a growing number of researchers have begun to study online social cognition, i.e. social cognition from a participant's point of view, based on the assumption that there is something fundamentally different when we are actively engaged with others in real-time social interaction as compared to when we merely observe them. Whereas, for offline social cognition, interaction and feedback are merely a way of gathering data about the other person that feeds into processing algorithms 'inside’ the agent, it has been proposed that in online social cognition the knowledge of the other —at least in part— resides in the interaction dynamics ‘between’ the agents. Furthermore being a participant in an ongoing interaction may entail a commitment toward being responsive created by important differences in the motivational foundations of online and offline social cognition. In order to promote the development of the neuroscientific investigation of online social cognition, this Frontiers Research Topic aims at bringing together contributions from researchers in social neuroscience and related fields, whose work involves the study of at least two individuals and sometimes two brains, rather than single individuals and brains responding to a social context. Specifically, this Research Topic will adopt an interdisciplinary perspective on what it is that separates online from offline social cognition and the putative differences in the recruitment of underlying processes and mechanisms. Here, an important focal point will be to address the various roles of social interaction in contributing to and —at times— constituting our awareness of other minds. For this Research Topic, we, therefore, solicit reviews, original research articles, opinion and method papers, which address the investigation of social interaction and go beyond traditional concepts and ways of experimentation in doing so. While focusing on work in the neurosciences, this Research Topic also welcomes contributions in the form of behavioral studies, psychophysiological investigations, methodological innovations, computational approaches, developmental and patient studies. By focusing on cutting-edge research in social neuroscience and related fields, this Frontiers Research Topic will create new insights concerning the neurobiology of social interaction and holds the promise of helping social neuroscience to really go social.
It has become clear to researchers in robotics and adaptive behaviour that current approaches are yielding systems with limited autonomy and capacity for self-improvement. To learn autonomously and in a cumulative fashion is one of the hallmarks of intelligence, and we know that higher mammals engage in exploratory activities that are not directed to pursue goals of immediate relevance for survival and reproduction but are instead driven by intrinsic motivations such as curiosity, interest in novel stimuli or surprising events, and interest in learning new behaviours. The adaptive value of such intrinsically motivated activities lies in the fact that they allow the cumulative acquisition of knowledge and skills that can be used later to accomplish fitness-enhancing goals. Intrinsic motivations continue during adulthood, and in humans they underlie lifelong learning, artistic creativity, and scientific discovery, while they are also the basis for processes that strongly affect human well-being, such as the sense of competence, self-determination, and self-esteem. This book has two aims: to present the state of the art in research on intrinsically motivated learning, and to identify the related scientific and technological open challenges and most promising research directions. The book introduces the concept of intrinsic motivation in artificial systems, reviews the relevant literature, offers insights from the neural and behavioural sciences, and presents novel tools for research. The book is organized into six parts: the chapters in Part I give general overviews on the concept of intrinsic motivations, their function, and possible mechanisms for implementing them; Parts II, III, and IV focus on three classes of intrinsic motivation mechanisms, those based on predictors, on novelty, and on competence; Part V discusses mechanisms that are complementary to intrinsic motivations; and Part VI introduces tools and experimental frameworks for investigating intrinsic motivations. The contributing authors are among the pioneers carrying out fundamental work on this topic, drawn from related disciplines such as artificial intelligence, robotics, artificial life, evolution, machine learning, developmental psychology, cognitive science, and neuroscience. The book will be of value to graduate students and academic researchers in these domains, and to engineers engaged with the design of autonomous, adaptive robots. The contributing authors are among the pioneers carrying out fundamental work on this topic, drawn from related disciplines such as artificial intelligence, robotics, artificial life, evolution, machine learning, developmental psychology, cognitive science, and neuroscience. The book will be of value to graduate students and academic researchers in these domains, and to engineers engaged with the design of autonomous, adaptive robots.